Cite
A framework for predicting variable-length epitopes of human-adapted viruses using machine learning methods.
MLA
Yin, Rui, et al. “A Framework for Predicting Variable-Length Epitopes of Human-Adapted Viruses Using Machine Learning Methods.” Briefings in Bioinformatics, vol. 23, no. 5, Sept. 2022. EBSCOhost, https://doi.org/10.1093/bib/bbac281.
APA
Yin, R., Zhu, X., Zeng, M., Wu, P., Li, M., & Kwoh, C. K. (2022). A framework for predicting variable-length epitopes of human-adapted viruses using machine learning methods. Briefings in Bioinformatics, 23(5). https://doi.org/10.1093/bib/bbac281
Chicago
Yin, Rui, Xianghe Zhu, Min Zeng, Pengfei Wu, Min Li, and Chee Keong Kwoh. 2022. “A Framework for Predicting Variable-Length Epitopes of Human-Adapted Viruses Using Machine Learning Methods.” Briefings in Bioinformatics 23 (5). doi:10.1093/bib/bbac281.